Integral sliding mode control for active suspension systems of half-vehicle model

Abstract

This paper proposes a design method of sliding mode controller with the robustness against actuator uncertainty for active suspension systems of half-vehicle model. The features of the proposed sliding mode controller are not to require any force sensors to constitute local force feedback loop and to avoid chattering, which will be often a problem in sliding mode control. Based on the concept of the second order sliding mode control, the switching control input is redesigned by the describing function method in order to occur limit cycles of the switching function. Occurring the limit cycles instead of perfect sliding mode can lead continuous control inputs to suppress deterioration in high frequency band. The describing function method shows the existing condition of the limit cycles for the design parameters of the redesigned switching input. From numerical simulations, it can be checked that the proposed sliding mode controller can occur almost desired limit cycles of the switching function. Also, it can be seen that the proposed sliding mode controller shows high robustness against actuator uncertainty while it can suppress chattering in high frequency band.

Study on Active Suspension with Variable Structure Control Based on the Fractional Order Exponential Reaching Law

“…Because the fractional order operator is better than the traditional integer order operator, it has better robustness and the ability of the system. At present, there are some achievements on the research of fractional sliding mode control in vehicle suspension control, but they are still in the initial stage [12][13][14][15][16][17]. From the previous research on suspension sliding mode control, the research and application is not using fractional order exponential reaching law sliding mode controller design.…”

Research on variable universe fuzzy PID control for semi-active suspension with CDC dampers based on dynamic adjustment functions

“…For the design and optimization of semi-active suspension controllers, researchers have proposed the optimal control, sliding mode control, PID control, neural network control, fuzzy control [3][4][5][6] . For example, Attia et al 7 designed a linear quadratic regulator (LQR) based on the optimal control theory to improve the smoothness of vehicles and maintain the stability of roads, but its robustness is poor.…”